{"id":"W2040181029","doi":"10.1097/01.opx.0000221403.32040.17","title":"Novel Pachometry Calibration","year":2006,"lang":"en","type":"article","venue":"Optometry and Vision Science","topic":"Corneal surgery and disorders","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Calibration; Computer science; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004561411,0.00006536806,0.0001025895,0.00036788,0.0002043524,0.00007622048,0.00005386762,0.00003541221,0.00008688154],"category_scores_gemma":[0.0001503219,0.00005067558,0.00002671421,0.002035125,0.0002788957,0.0003894054,0.00004644746,0.00006679242,0.000009819915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001507697,"about_ca_system_score_gemma":0.00004816979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002858641,"about_ca_topic_score_gemma":5.228478e-7,"domain_scores_codex":[0.9990965,0.000005573758,0.0001264158,0.0002520538,0.0003485871,0.0001708884],"domain_scores_gemma":[0.9995893,0.00006485661,0.00003246261,0.0001403729,0.0000546829,0.00011832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001062048,0.0003455245,0.5914186,0.0000472721,0.000002466302,0.00000606289,0.00003580616,0.00001552423,0.3497948,0.002191227,0.0008847175,0.05515183],"study_design_scores_gemma":[0.0005197375,0.0001073757,0.9822459,0.00003345642,0.000007334472,0.00004523183,0.00006888591,0.004285899,0.009357499,0.0001269413,0.003103292,0.00009846144],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782514,0.0001733632,0.01132925,0.0004776953,0.0001199179,0.00007277114,0.000002116607,0.00003533369,0.009538156],"genre_scores_gemma":[0.9978074,0.00001393089,0.001259657,0.0003217348,0.00005020251,0.000001464787,0.000004255144,0.000003316199,0.0005379819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3908273,"threshold_uncertainty_score":0.206649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0152880907114151,"score_gpt":0.3897533846674879,"score_spread":0.3744652939560728,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}